The NIGA with the Clustering Idea for Solving the Packing Problem in the Hull Construction Automatic Packing System

Author

Ying, Mei ; Liangsheng, Zhu ; Ye Jiawei

Author_Institution

Coll. of Traffic & Commun., SCUT, Guangzhou, China

fYear

2009

fDate

13-14 Dec. 2009

Firstpage

361

Lastpage

364

Abstract

The paper discusses the irregular parts packing problem based on an improved immune genetic algorithm, and a NIGA based on crowing mechanism is proposed. For improving the packing efficiency, the clustering idea and algorithm are introduced and the effective characteristics of matching packing-graphics are extracted and analyzed. GA, an improved immune genetic algorithm, and NIGA are applied to practical experiments respectively to solve the packing problem and optimize the results, and we compare the results. In solving the large-scale packing problem, the application of immunity operator and niche genetic algorithm based on crowing mechanism improves the global optimization performance and velocity of convergence. The improved algorithms are effective and feasibility for solving the hull construction automatic packing problem.

Keywords

bin packing; computational complexity; convergence; genetic algorithms; clustering idea; convergence velocity; crowing mechanism; global optimization performance; hull construction automatic packing system; immunity operator; irregular parts packing problem; niche immune genetic algorithm; packing-graphics matching; Algorithm design and analysis; Clustering algorithms; Data mining; Genetic algorithms; Graphics; Heuristic algorithms; Large-scale systems; MATLAB; Sheet materials; Stochastic processes; clustering idea; immune genetic algorithm; niche skill; packing optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Future Information Technology and Management Engineering, 2009. FITME '09. Second International Conference on

Conference_Location

Sanya

Print_ISBN

978-1-4244-5339-9

Type

conf

DOI

10.1109/FITME.2009.96

Filename

5381002